Research Paper Summary Prompt
Objective, Methodology, Findings, Limitations — paper summaries that keep the findings tied to the caveats that constrain them.
Overview
The classic failure of AI paper summaries is amputating the limitations: findings arrive confident, caveats vanish, and the literature review inherits claims the authors never made. This setup summarizes papers into four sections where Findings and Limitations travel together, under Strict Fidelity — no unsupported conclusions, key numbers as written — with Important Quotes for the claims that deserve exact wording. The reading guidance states the academic reality: the abstract and conclusion state the claims; the methods and limitations decide how much to trust them.
Workflow
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One paper per summary
Per-paper records keep the literature review traceable — every claim links to its source.
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Read Findings and Limitations together
The skeleton places them adjacent on purpose: a finding without its constraint is a different claim.
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Quote the load-bearing claims
Important Quotes keeps the sentences you'll cite verbatim — paraphrased claims drift.
Why This Works
- A Limitations section the model MUST fill stops the classic caveat amputation
- Strict fidelity bans the upgrade from "suggests" to "shows"
- Methodology in the skeleton forces the trust-calibrating context into every summary
Best for
- Researchers screening papers at volume
- Evidence-based teams who cite what they summarize
- Anyone burned by a summary stronger than the paper
Not for
- Critiquing the methodology — the summary reports it; the judgment is yours
- Extracting citation metadata as data — that's extraction
Use cases
- Building literature reviews from a stack of papers
- Keeping effect sizes and sample numbers exactly as published
- Carrying limitations alongside findings instead of dropping them